Software Engineering Intern, Distributed Scientific Computing Libraries - Fall 2025

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!

We are looking for a software engineering intern to work on CuPyNumeric, a drop-in distributed, accelerated replacement for NumPy. As a member of our team, you will use your design abilities, coding expertise, and creativity to develop distributed and GPU-accelerated versions of NumPy and SciPy methods and other scientific computing libraries. You will also have the opportunity to enhance the functionality and performance of runtime systems that underlay the foundation of distributed GPU computing at NVIDIA. Specifically, you will be working to:

What you'll be doing:

• Improving performance by developing highly optimized and innovative algorithms for high performance numerical computing.
• Architect, prioritize, and develop new features in cuPyNumeric and the runtime stack
• Designing future-proof API’s for accelerated numerical/scientific computing libraries.
• Contribute to the development of runtime systems that underlay the foundation of multi-GPU computing at NVIDIA.
• Write effective, maintainable, and well-tested code for production use.

What we need to see:

• Pursuing BS, MS, or PhD degree in Computer Science, Electrical Engineering, or related field
• Strong foundation in modern C++ best practices and object oriented programming.
• Experience using Python for numerical computing (e.g. NumPy, SciPy).
• Experience with CUDA C++.
• Academic knowledge of tasking or asynchronous runtimes, especially data-centric initiatives such as Legion
• Good written communication, teamwork, and presentation skills.

Ways to stand out from the crowd:

• Proficiency in C++17 and beyond.
• Experience in Python binding technology for C++, particularly pybind11 or nanobind.
• Experience using C++ tooling and linters such as clang-tidy, libclang, or similar.
• Experience building, debugging, profiling and optimizing distributed applications, on supercomputers or the cloud.
• Prior experience in open source HPC software development.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

The hourly rate for our interns is 18 USD - 71 USD. Our internship hourly rates are a standard pay determined based on the position and your location, year in school, degree, and experience.

You will also be eligible for Intern benefits. NVIDIA accepts applications on an ongoing basis. ​

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.